{"id":"https://openalex.org/W2918689195","doi":"https://doi.org/10.1109/tencon.2018.8650316","title":"Affine Differential Local Mean ZigZag Pattern for Texture Classification","display_name":"Affine Differential Local Mean ZigZag Pattern for Texture Classification","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2918689195","doi":"https://doi.org/10.1109/tencon.2018.8650316","mag":"2918689195"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2018.8650316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087427076","display_name":"Swalpa Kumar Roy","orcid":"https://orcid.org/0000-0002-6580-3977"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swalpa Kumar Roy","raw_affiliation_strings":["JGEC, Jalpaiguri, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JGEC, Jalpaiguri, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079034948","display_name":"Dipak Ghosh","orcid":"https://orcid.org/0000-0003-3768-8091"},"institutions":[{"id":"https://openalex.org/I3130244785","display_name":"Adamas University","ror":"https://ror.org/02tne2741","country_code":"IN","type":"education","lineage":["https://openalex.org/I3130244785"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dipak Kumar Ghosh","raw_affiliation_strings":["Adamas University, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adamas University, India","institution_ids":["https://openalex.org/I3130244785"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037279956","display_name":"Rajat Kumar Pal","orcid":"https://orcid.org/0000-0001-9838-6500"},"institutions":[{"id":"https://openalex.org/I106542073","display_name":"University of Calcutta","ror":"https://ror.org/01e7v7w47","country_code":"IN","type":"education","lineage":["https://openalex.org/I106542073"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajat Kumar Pal","raw_affiliation_strings":["University of Calcutta, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Calcutta, India","institution_ids":["https://openalex.org/I106542073"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025093894","display_name":"B.B. Chaudhuri","orcid":"https://orcid.org/0000-0003-0297-8929"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bidyut B. Chaudhuri","raw_affiliation_strings":["ISI, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ISI, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.106,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.50136376,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"0488","last_page":"0493"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9749000072479248,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.7110514640808105},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.6958192586898804},{"id":"https://openalex.org/keywords/zigzag","display_name":"Zigzag","score":0.6799298524856567},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6641464233398438},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6392703652381897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5318137407302856},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.47926637530326843},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4707896113395691},{"id":"https://openalex.org/keywords/affine-combination","display_name":"Affine combination","score":0.42898499965667725},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.23966684937477112},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17349734902381897},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.13031813502311707}],"concepts":[{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7110514640808105},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.6958192586898804},{"id":"https://openalex.org/C192271897","wikidata":"https://www.wikidata.org/wiki/Q198438","display_name":"Zigzag","level":2,"score":0.6799298524856567},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6641464233398438},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6392703652381897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5318137407302856},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.47926637530326843},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4707896113395691},{"id":"https://openalex.org/C207221997","wikidata":"https://www.wikidata.org/wiki/Q938614","display_name":"Affine combination","level":3,"score":0.42898499965667725},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.23966684937477112},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17349734902381897},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.13031813502311707}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2018.8650316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W151368118","https://openalex.org/W1516748092","https://openalex.org/W1985636418","https://openalex.org/W1994607143","https://openalex.org/W2000123870","https://openalex.org/W2021751319","https://openalex.org/W2028735463","https://openalex.org/W2031586513","https://openalex.org/W2039051707","https://openalex.org/W2044465660","https://openalex.org/W2052446636","https://openalex.org/W2058021621","https://openalex.org/W2078818280","https://openalex.org/W2098347925","https://openalex.org/W2103496373","https://openalex.org/W2106145073","https://openalex.org/W2108082645","https://openalex.org/W2112020727","https://openalex.org/W2126833203","https://openalex.org/W2131081720","https://openalex.org/W2147141800","https://openalex.org/W2152548630","https://openalex.org/W2158698691","https://openalex.org/W2159988601","https://openalex.org/W2163352848","https://openalex.org/W2164039212","https://openalex.org/W2172000360","https://openalex.org/W2215003561","https://openalex.org/W2510824196","https://openalex.org/W2791977337","https://openalex.org/W2886468927","https://openalex.org/W2904495085","https://openalex.org/W2911956715","https://openalex.org/W2964082530","https://openalex.org/W2964152499","https://openalex.org/W4255747608","https://openalex.org/W4293768955","https://openalex.org/W6746553287"],"related_works":["https://openalex.org/W2122718025","https://openalex.org/W2342684998","https://openalex.org/W2181817726","https://openalex.org/W2471967074","https://openalex.org/W4235736048","https://openalex.org/W3024593842","https://openalex.org/W1990254706","https://openalex.org/W2084469691","https://openalex.org/W2537156416","https://openalex.org/W2795417921"],"abstract_inverted_index":{"The":[0,29,77,134,152],"texture":[1,27,126,163,170],"classification":[2,171],"is":[3,42,80,129,138],"a":[4,16,61,67,125],"significant":[5],"problem":[6],"in":[7,60,103],"the":[8,46,94,142,168],"area":[9],"of":[10,124,144],"pattern":[11],"recognition.":[12],"This":[13],"work":[14],"proposes":[15],"novel":[17],"Affine":[18,146],"Differential":[19,147],"Local":[20,36,148],"Mean":[21,37,149],"ZigZag":[22,38,62,150],"Pattern":[23,39],"(ADLMZP)":[24],"descriptor":[25,70,95,137],"for":[26],"classification.":[28],"proposed":[30],"method":[31],"has":[32],"two":[33],"manifolds:":[34],"first":[35],"(LMZP)":[40],"map":[41],"calculated":[43],"by":[44,82,140],"thresholding":[45],"3":[47,49],"\u00d7":[48],"patch":[50],"neighbor":[51,84],"intensity":[52,85],"values":[53,86],"with":[54,87,119,167],"respect":[55,88],"to":[56,72,89,105,109],"path":[57,90],"mean":[58,91],"but":[59],"weighting":[63],"fashion,":[64],"which":[65,92,128],"provides":[66],"well":[68,157],"discriminated":[69],"compared":[71,166],"other":[73],"local":[74,78],"binary":[75],"descriptors.":[76],"micropattern":[79],"obtained":[81],"comparing":[83],"makes":[93],"robust":[96],"against":[97],"noise":[98],"and":[99,161,165],"illumination":[100],"variations.":[101],"Secondly,":[102],"order":[104],"make":[106],"it":[107],"invariant":[108],"affine":[110,115,120],"changes,":[111],"we":[112],"incorporated":[113],"an":[114],"differential":[116],"transformation":[117],"along":[118],"gradient":[121],"magnitude":[122],"information":[123],"image":[127],"differed":[130],"from":[131],"Euclidean":[132],"Gradient.":[133],"final":[135],"ADLMZP":[136],"generated":[139],"concatenating":[141],"histograms":[143],"all":[145],"maps.":[151],"results":[153],"are":[154],"computed":[155],"over":[156],"known":[158],"KTH-TIPS,":[159],"Brodatz,":[160],"CUReT":[162],"datasets":[164],"state-of-the-art":[169],"methods.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}